This thesis describes the implementation of a covering algorithm for semantic decomposition of sentences of technical patents. This research complements the ASPIN project that has a long term goal of providing an automated system for digital system synthesis from patents. In order to develop a prototype of the system explained in a patent, a natural language processor (sentence-interpreter) is required. These systems typically attempt to interpret a sentence by syntactic analysis (parsing) followed by semantic analysis. Quite often, the technical narrative contains grammatical errors, incomplete sentences, anaphoric references and typological errors that can cause the grammatical parse to fail. In such situations, an alternate method that uses a repository of pre-compiled, simple sentences (called frames) to analyze the sentences of the patent can be a useful back up. By semantically decomposing the sentences of patents to a set of frames whose meanings are fully understood, the meaning of the patent sentences can be interpreted. This thesis deals with the semantic decomposition of sentences using a branch and bound covering algorithm. The algorithm is implemented in C++. A number of experiments were conducted to evaluate the performance of this algorithm. The covering algorithm uses a standard branch and bound algorithm to semantically decompose sentences. The algorithm is fast, flexible and can provide good (100 % coverage for some sentences) coverage results. The system covered 67.68 % of the sentence tokens using 3459 frames in the repository. 54.25% of the frames identified by the system in covers for sentences, were found to be semantically correct. The experiments suggest that the performance of the system can be improved by increasing the number of frames in the repository. / Master of Science

In manufacturing environments, machines are usually subject to down periods due to various reasons such as preventive maintenance activities, pre-accepted jobs and pre-known material shortages. Among these reasons, preventive maintenance, which is defined as the pre-planned maintenance activities to keep the machine in its operating state, has gained much more importance in recent years. In this thesis, we consider the single machine total flow time problem where the jobs are non-resumable and the machine is subject to preventive maintenance activities of known starting times and durations. We propose a number of optimality properties together with the upper and lower bounding procedures. Using these mechanisms, we build a branch and bound algorithm to find the optimal solution of the problem. Our extensive computational study on randomly generated test instances shows that our algorithm can solve large-sized problem instances with up to 80 jobs in reasonable times. We also study a two-alternative maintenance planning problem with minor and major maintenances. We give an optimizing algorithm to find the timing of the maintenances, when the job sequence is fixed.

The growing extent and variety of present military operations forces to use the resources in hand at its best. Especially, the optimum usage and assignment of limited number of the air force resources to missions will provide a considerable advantage in the battle field. The problem of finding the feasible and optimum assignment has been known to be studied / yet performing the process faster is still a topic that captures researchers&rsquo / attention because of the computational complexity that the assignment problem involves within. In this thesis, exploring the optimal assignment of fleets/aircrafts to targets/groups of targets is going to be performed via algorithms and heuristics. As the best choice for finding the exact solution, Branch-and-Bound algorithm, which is an intelligent way of searching for the solution on a solution tree where the nodes with potential of not leading to the solution are fathomed, has been investigated and applied according to the specific problem needs. The number of nodes on the search tree increases exponentially as the problem size increases. Moreover / as the size of the assignment problem increases, attaining the solution solely by Branch-and-Bound algorithm is definitely computationally expensive due to memory and time requirements. Therefore, Genetic algorithm which can provide good solutions in a relatively short time without having computational difficulties is considered as the second algorithm. Branch-and-Bound algorithm and Genetic algorithm are separately used for obtaining the solution. Hybrid algorithms which are combinations of Branch-and-Bound and Genetic algorithms are used with heuristics for improving the results.

ABSTRACT FLEXIBLE ASSEMBLY LINE DESIGN PROBLEM WITH FIXED NUMBER OF WORKSTATIONS Barut&ccedil / uoglu, Sirin M.S. Department of Industrial Engineering Supervisor: Prof. Dr. Meral Azizoglu July 2009, 70 pages In this thesis, we study a Flexible Assembly Line Design problem. We assume the task times and equipment costs are correlated in the sense that for all tasks the cheaper equipment gives no smaller task time. Given the cycle time and number of workstations we aim to find the assignment of tasks and equipments to the workstations that minimizes the total equipment cost. We study a special case of the problem with identical task times. For the general case, we develop a branch and bound algorithm that uses powerful lower bounds and reduction mechanisms. We test the performance of our branch and bound algorithm on randomly generated test problems. The results of our experiments have revealed that we are able to solve large-sized problem instances in reasonable times.

In this thesis, we develop an exact algorithm for an assembly line balancing problem with equipment selection decisions. Two objectives are considered: minimizing the total equipment costs and the number of workstations. Our aim is to choose the type of the equipment(s) in every workstation and determine the assignment of the tasks to each workstation and equipment type. We aim to propose a set of efficient solutions for each problem and leave the choice of the best solution to the decision maker&rsquo / s preferences. A branch and bound algorithm is developed whose efficiency is increased with some dominance rules and powerful lower bounds. Moreover, modified ranked positional weight heuristic method is used as initial upper bound. The effectiveness of the proposed procedure is demonstrated by computational analysis in which the effects of changing certain parameter values are investigated. We find that our algorithm is capable of solving the problem instances with up to 25 tasks and 5 equipments.

In this study, we consider the disassembly problem of end-of-life (EOL) products for recovering valuable parts or assemblies. All parts obtained by disassembly processes of an EOL product may not be profitable due to their high recovery costs. Our problem is to select the parts to be released and determine the associated disassembly tasks so as to maximize the total profit. We first tackle the simple part selection problem, and then introduce a time constraint for the tasks to be performed for selected parts and search for incomplete time constrained sequences. We formulate our first problem as a Mixed Integer Problem and show that the constraint set of this formulation is totally unimodular. We also provide the dual formulation of our problem and its interpretation. For time-constrained part selection problem we propose a branch-and-bound algorithm. We first develop some reduction mechanism to reduce the size of the problem. Our solution procedure is capable of solving problems with up to 94 parts and tasks.

Orientadores: Ariovaldo Verandio Garcia, Marcos Julio Rider Flores / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de Computação / Made available in DSpace on 2018-08-15T23:19:01Z (GMT). No. of bitstreams: 1 Oliveira_MarinaLavoratode_D.pdf: 1360671 bytes, checksum: e66710c118252edf8c3638375c56fdc7 (MD5) Previous issue date: 2010 / Abstract: In this work the Distribution System Integrated Planning (DSIP) problem is modeled as a mixed integer (binary) nonlinear program problem. Two techniques were investigated to solve this problem. First, a specialized Constructive Heuristic Algorithm (CHA) was implemented. A sensitivity index is used in each step of the CHA to add a circuit, a substation, a capacitor bank or a voltage regulator to the distribution system. This sensitivity index is obtained by solving the DSIP problem considering the numbers of circuits and substations to be added as continuous variables (the DSIP relaxed problem). The objective of the DSIP is to minimize the operation costs and the construction costs of circuits, substations, capacitors and voltage regulators, which are subjected to constraints of power balance, voltage magnitude, maximum circuit and substation capacities, taps control and radiality constraint. In addition, a local improvement phase to improve the initial solution of the CHA and a branching technique to avoid the infeasibility cases in the distribution system operation were included / Doutorado / Energia Eletrica / Doutor em Engenharia Elétrica

Orientador: Paulo Augusto Valente Ferreira / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de Computação / Made available in DSpace on 2018-08-21T14:52:27Z (GMT). No. of bitstreams: 1 Ashtiani_AlirezaMohebi_D.pdf: 1381601 bytes, checksum: 9ae82bd53a7cf70422fed2348416f8f0 (MD5) Previous issue date: 2012 / Resumo: Muitos problemas práticos em Engenharia, Economia e Planejamento são modelados de maneira conveniente como problemas de Otimização Global. Esta tese tem como objetivo principal apresentar novas técnicas de Otimização Global com foco na resolução de duas importantes classes de problemas: problemas de Programação Multiplicativa Generalizada, os quais envolvem a minimização e a maximização de uma soma finita de produtos de funções convexas e côncavas, respectivamente, e problemas de Programação Fracionária Generalizada, os quais, por sua vez, envolvem a minimização e a maximização de uma soma finita de razões de funções convexa-côncava ou côncava-convexa, respectivamente. Na tese demonstra-se que todos estes problemas podem ser eficientemente resolvidos por um mesmo algoritmo de aproximação externa, a partir da reformulação dos problemas como problemas com infinitas restrições lineares de desigualdade. Um algoritmo baseado em enumeração de restrições e um algoritmo de aproximação externa combinado a uma técnica branch-and-bound são usados para resolver globalmente problemas de Programação Multiplicativa. Em seguida, as mesmas técnicas são empregadas na resolução de problemas de Programação Fracionária. Experiências computacionais atestam a viabilidade e a eficiência dos métodos de Otimização Global propostos, os quais também são facilmente programáveis a partir de pacotes de otimização disponíveis comercialmente / Abstract: Many practical problems in Engineering, Economics and Planning are modeled in a convenient way by Global Optimization problems. The principal objective of this thesis is to introduce new global optimization techniques with focus on the resolution of two important classes of problems: Generalized Multiplicative Programming Problems, in which involve the minimization and maximization of a finite sum of products of convex and concave functions, respectively, and Generalized Fractional Programming Problems, in which, in turn, involve the minimization and maximization of a finite sum of convex-concave and concave-convex ratio functions, respectively. The thesis demonstrates that all these problems can be efficiently solved by the same outer approximation algorithm, from the reformulation of the problems as problems with infinite linear inequality constraints. An algorithm based on a constraint enumeration and an outer approximation algorithm together with a branch-and-bound technique are used to globally solve Multiplicative Programming problems. Then, the same techniques are employed in the resolution of Fractional Programming problems. Computational experiments certify the viability and efficiency of the proposed Global Optimization methods, which are also easily programmable through commercially available optimization packages / Doutorado / Automação / Doutor em Engenharia Elétrica

京都大学 / 新制・課程博士 / 博士(情報学) / 甲第23322号 / 情博第758号 / 新制||情||129(附属図書館) / 京都大学大学院情報学研究科数理工学専攻 / (主査)教授 永持 仁, 教授 太田 快人, 教授 山下 信雄 / 学位規則第4条第1項該当 / Doctor of Informatics / Kyoto University / DFAM

Étant donné G = (V, E) un graphe non orienté connexe et un entier positif β (n), où n est le nombrede sommets de G, le problème du séparateur (VSP) consiste à trouver une partition de V en troisclasses A, B et C de sorte qu'il n'y a pas d'arêtes entre A et B, max {| A |, | B |} est inférieur ou égal àβ (n) et | C | est minimum. Dans cette thèse, nous considérons une modélisation du problème sous laforme d'un programme linéaire en nombres entiers. Nous décrivons certaines inégalités valides et etdéveloppons des algorithmes basés sur un schéma de voisinage.Nous étudions également le problème du st-séparateur connexe. Soient s et t deux sommets de Vnon adjacents. Un st-séparateur connexe dans le graphe G est un sous-ensemble S de V \ {s, t} quiinduit un sous-graphe connexe et dont la suppression déconnecte s de t. Il s'agit de déterminer un stséparateur de cardinalité minimum. Nous proposons trois formulations pour ce problème et donnonsdes inégalités valides du polyèdre associé à ce problème. Nous présentons aussi une heuristiqueefficace pour résoudre ce problème. / Given G=(V,E) a connected undirected graph and a positive integer β(n), where n is number ofvertices, the vertex separator problem (VSP) is to find a partition of V into three classes A,B and Csuch that there is no edge between A and B, max{|A|,|B|}less than or equal β(n), and |C| isminimum. In this thesis, we consider aninteger programming formulation for this problem. Wedescribe some valid inequalties and using these results to develop algorithms based onneighborhood scheme.We also study st-connected vertex separator problem. Let s and tbe two disjoint vertices of V, notadjacent. A st-connected separator in the graph G is a subset S of V\{s,t} such that there are no morepaths between sand tin G[G\S] and the graph G[S] is connected . The st-connected vertex speratorproblem consists in finding such subset with minimum cardinality. We propose three formulationsfor this problem and give some valid inequalities for the polyhedron associated with this problem.We develop also an efficient heuristic to solve this problem.